Algorithm for predicting outcome based on parameters

Question

I've never done anything with statistics, so I'm unsure of how to start with this problem that I need to solve for some software that I'm working on.

Basically, there are three parameters

1. An integer parameter (A) that can be a range of (for the sake of argument) 1-10
2. A Boolean parameter (B) that if present weights the value of A.
3. An integer parameter (C) that can be a range of 1-100.

There is one outcome: An integer (D) that can be of the range -1, 0, 1.

For each value of C, there will be one value of A, B, and D. C is a preexisting condition. A, and B are parameters. D is the outcome, which may be subjective.

+---+----+---+----+
| C | A  | B | D  |
+---+----+---+----+
| 1 |  3 | 0 | -1 |
| 1 |  3 | 1 | -1 |
| 1 |  5 | 0 |  0 |
| 1 |  5 | 0 |  0 |
| 1 | 10 | 0 |  1 |
| 1 | 10 | 1 |  1 |
| 2 |  3 | 0 | -1 |
| 2 |  3 | 1 |  0 |
| 2 |  4 | 0 |  0 |
| 2 |  4 | 1 |  0 |
+---+----+---+----+

What I'm looking for, is given C, A, B, how can I make a prediction of what D will be. In this case, I will have historical data of all four values to go from. C won't necessarily be linear as in my example.

Answer 1

This is a supervised learning problem.

It seems to be a classification task i.e. the output variable D takes class labels (the other group is the regression task).

There are a lot of algorithms for classification and you should probably start with something simple e.g. logistic regression.

If I misunderstood the example and yours is a symbolic regression task, a good approach is genetic programming (you have to specify a set of primitive and new equations are then formed by recombining previous equations).